The unvarnished truth

It is not only Google or Facebook who are able to analyze images using artificial intelligence. Control Expert, a German SME, automatically recognizes and calculates damage from photos of the accident.

Fall foliage stretches the algorithm to its limits. When leaves are lying on the road they are easily reflected in the bumper of a car – and developers still need to teach the algorithm that it is not car body damage. In the meantime, apart from such mistakes, the computer program is quite good at estimating an insurance customer’s claim after a motor accident. Nicolas Witte trained it with millions of sample photos of car body damage and historical data regarding the extent of such damage, thus teaching it to read the images automatically and to draw the right conclusions. Witte manages Control Expert, who handle claims resulting from car accidents on behalf of insurance companies. This entails checking motor vehicle assessments made by appraisers, as well as invoices and cost estimates from repair shops. His algorithm enables more than 800 employees worldwide to deal with all that in just a few hours now - it used to take weeks. With that, the service provider based in Langenfeld in the Rhineland possesses a technology in a field where giants like Google or Facebook usually keep to themselves. For example, the social network automatically provides suggestions about who might be on the photos to anyone uploading photos. If you tag the relevant people, the algorithm will continue to learn, thus sharpening its skills. Google, the search engine provider, now browses the internet itself looking for photos and offers different models and algorithms for machine learning in the cloud since early last year. For instance, Google AI helps the Zoological Society of London, a conservation organization, to assign photos from their own camera traps in reserves to the relevant animals automatically. They do this by using tags in their own database. However, Control Expert developed their algorithms themselves – showing that SMEs are technologically quite capable of keeping up with the US companies, if only they use their niche effectively. Under blue light, Nicolas Witte’s treasure makes a quiet whirring sound behind a pane of glass on the ground floor of the company. In a way, this is the brain of the artificial intelligence (AI), which estimates the insurance customers‘ claims: 600 servers, powered by a total of 750 processors as well as special graphic chips plus two petabytes of stored photo data. If Witte tried to store all these photos on DVDs and piled them up, the pile would be about 500 meters high. Daniel Kröll works as a data scientist in the research department at Control Expert, along with more than 20 colleagues made up of astrophysicists, mathematicians and computer scientists. He shows how good AI now is at handling car body damage. First Kröll drags the photo of a vehicle registration into a mask of the web-based software.

Vehicle registration or treasure map

Then the algorithm reads the vehicle identification number – with that every car can be clearly matched. “That seems to be trivial, but it is mega complicated“, emphasizes Kröll. “After 20 years, a lot of vehicle registration documents look like treasure maps.“ Google’s algorithms did not suffice for exactly these special forms of image recognition. Because this company from the Rhineland was working on finding a new approach, their Speed Check software already recognizes the car’s identification number with an accuracy level of more than 90 percent today.

In the next step, Kröll uploads several photos of a damaged white BMW onto the web-based software. Within split seconds, it analyzes which parts of the car it recognizes on the photos, identifies damaged parts and determines the severity of the respective damage. Ultimately, an automatically generated calculation with digital sketches of the car, including the damaged parts shown in color, appears under the photos. The algorithm already works so precisely that it recognizes, for instance, whether a fender only has to be painted after an accident, or also straightened out or even replaced completely. This already works in 80 to 90 percent of all claims, according to Kröll. In 2015, researchers from Facebook and the University of California in Berkeley presented a new type of image analysis that is able to identify people with 83 percent accuracy; this process is still not in practice today. This company from the Rhineland with their AI is one of the pioneers of digitization for insurance companies – but not the only provider which uses technology to speed up the claims handling process: Omni:us, a Berlin-based startup, is specialized in digitizing insurers’ customer inquiries, which used to be handled manually, and processing them automatically. In addition, they rely on artificial intelligence too. According to the company, eight of the ten largest insurers worldwide already use their software. The company with 40 employees, which was founded in 2015 by Sofie Quidenus-Wahlforss, an Austrian, was able to collect almost 20 million euros of risk capital at the end of November. Control Expert’s AI is also already working so well that 20 insurers from 16 countries use this service. The process is very easy for insurance companies’ customers: they have to upload at least four photos of their damaged vehicle from different perspectives via internet or an app – everything else works mostly automatic.

“As a result of the algorithm handling a multitude of volume damage automatically, our employees have got more time for more complicated cases“, as pointed out by Witte, the company boss. “So AI should not make people redundant.“ Even in cases of damage which are difficult to assess, and where employees have to intervene manually, the appraisal is finished within two hours. This used to take two weeks. So fast that some insurers deliberately hold the damage assessment results back for 90 minutes: “Some customers do not trust the result if the appraisal is ready after only a few minutes“, explains Witte.

A sensor measures data from the accident

For a long time now, the company’s data scientists have been working on speeding the claims handling process up even more. “Even before a car comes to a standstill after an accident, the system would already be able to determine the amount of damage“, Witte outlines his vision. After all, every modern car now has several sensors, for example for the engine, chassis or brakes. If the system manages to read the data in real time, it can already make many conclusions about the events leading up to an accident, and the damage involved. Control Expert is already reputedly negotiating with several car manufacturers – not a simple undertaking, the corporations want to develop new segments of business with their own data too after all. Until these complicated negotiations lead to a result sometime, the data scientist Stephen Seiler gets by with two electric model cars, which are only a bit larger than a human hand. You can see a silver-colored Mercedes and a red Audi, with a small plate with a radio antenna mounted on the roof, on the desk of this employee who studied electrical engineering. “That is a sensor which measures acceleration in three spatial dimensions when an accident occurs“, explains Seiler – and makes the mini Mercedes crash into the driver’s side of the Audi. The Speed Check software immediately appears on the monitor of his computer, fed with data from the sensor this time. “Someday we will be allowed to read the data straight from sensors in real cars too”, says Seiler. “Then automatic appraisals will work even more precisely.“ Not only with small toy cars, but on the road as well. For that, skills are necessary which even the best AI cannot help with yet: negotiating skills and perseverance.